Conventionally software organizations rely on human resources for knowledge acquisition, sharing and application of the knowledge in numerous ways. In service and support industries, enormous amount of the knowledge is available, mainly with human resources. The knowledge is utilized for analysis and resolution of problems arising in routine service and support work. Hence, there is a need for managing the knowledge hidden in the human resources and the knowledge residing in current implementations. More particularly there is a need to share and document tacit knowledge in the human resources and the knowledge available in the current software implementations to make the knowledge available and reusable. Modeling brings in a methodical way of structuring the knowledge enabling reusability of the knowledge. Modeling of the knowledge also means that there is no more hidden knowledge in individuals and in documents, scripts, implementations and configurations.
Some part of the knowledge in the service industries is available in the form of executables like scripts, runbooks and in the software implementations and configurations. While the other part of the knowledge resides in the human resources in the form of tacit knowledge. There is no effective way existing in the art to make the tacit knowledge and the knowledge in the documents, scripts, software implementations and configurations reusable and maintainable in the service industries. The knowledge developed for issue/request resolutions in the service industry is not uniform and is very specific to underlying technologies. For example, the knowledge of a database, captured for installation of the database on an operating system, is very specific to the underlying operating system. Hence, the knowledge capturing specific to the underlying technology creates duplication of knowledge. For example, there is duplication of knowledge for Oracle™ installed on Windows™ and Oracle™ installed on Linux™. The duplication of the knowledge in every place, throughout the organization, has detrimental effects. Further, the knowledge is not uniform or in standardized form, in all places of the organization. This results in loss of memory space or improper use of memory space.
Non-uniformity of the knowledge arises due to a fact that rules for creating the knowledge are either not defined or are not standardized. For example, the knowledge for checking file existence can be named in various ways as ‘CheckFileExistence’ or ‘CheckFile’ or ‘CheckFileExists’ or any other similar name. The knowledge is a part of many different individuals and comes from a large number of authors. Hence, involvement of the large number of authors results in the non-uniformity of the knowledge. It is imperative to address challenges related to the non-uniformity of the knowledge and duplication of the knowledge to avoid hurdles of crowd sourcing of the knowledge.